Despite the growing popularity of digital twin (DT) developments, there is a lack of common understanding and definition for important concepts of DT. It is needed to address this gap by building a shared understanding of DT before it becomes an obstacle for future work. With this challenge in view, the objective of our study is to assess the existing DT from various domains on a common basis and to unify the knowledge and understanding of DT developers and stakeholders before practice. To achieve this goal, we conducted a systematic literature review and analyzed 25 selected papers to identify and discuss the characteristics of existing DT's. The review shows an inconsistency and case-specific choices of dimensions in assessing DT. Therefore, this article proposes a four-dimensional evaluation framework to assess the maturity of digital twins across different domains, focusing on the characteristics of digital models. The four identified dimensions in this model are Capability, Cooperability, Coverage, and Lifecycle. Additionally, a weight mechanism is implemented inside the model to adapt the importance of each dimension for different application requirements. Several case studies are devised to validate the proposed model in general, industrial and scientific cases.

翻译：尽管数字孪生（DT）开发日益普及，但对DT重要概念仍缺乏共识与统一定义。在DT成为未来工作障碍之前，亟需通过构建共同理解来填补这一空白。基于此挑战，本研究旨在统一评估不同领域的现有DT，并在实践前整合DT开发者与利益相关者的知识认知。为实现该目标，我们开展了系统性文献综述，对25篇精选论文进行分析，识别并讨论了现有DT的特征。综述表明，现有DT评估维度存在不一致性与案例特定选择现象。因此，本文提出一个四维评估框架，聚焦数字模型特征，评估跨领域数字孪生的成熟度。该模型的四个维度分别为：能力（Capability）、协同性（Cooperability）、覆盖度（Coverage）与生命周期（Lifecycle）。此外，模型内置权重机制，可针对不同应用需求调整各维度重要性。通过多个案例研究，分别在通用场景、工业场景与科学场景中验证了所提模型的有效性。